On a previous post we learned how to train a machine learning classifier that is able to detect the different aspects mentioned on hotel reviews. With this aspect classifier, we were able to automatically know if a particular review was talking about cleanliness, comfort & facilities, food, Internet, location, staff and/or value for money. We also learned …
Rendering and processing complex documents online is a bit of a personal pet peeve of mine. When dealing with certain layouts, it can quickly become a very tough nut to crack. In the following 2 articles I will describe a technique of creating complex documents online using the open source DTP package Scribus, Python and a simple demo service written in Flask.
A few days ago, Ned Batchelder's post on deleting code made the rounds on HN, even though it was originally written in 2002. Here I want to echo a few of Ned's points, and take a stronger stance than he did: delete code as soon as you know you don't need it any more, no questions asked. I'll also offer some tips from the trenches for how to identify candidate dead code. This is the second in an ongoing series on eating your vegetables in software engineering, on good, healthy practices for a happy and successful codebase. I don't (yet) know how long the series will be, so please stay tuned!
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